Joan Lu

An order-clique-based approach for mining maximal co-locations

Most algorithms for mining spatial co-locations adopt an Apriori-like approach to generate size-k prevalence co-locations after size-(k-1) prevalence co-locations. However, generating and storing the co-locations and table instances is costly. A novel order-clique-based approach for mining maximal co-locations is proposed in this paper. The efficiency of the approach is achieved by two techniques: (1) the spatial neighbor relationships and the size-2 prevalence co-locations are compressed into extended prefix-tree structures, which allows the order-clique-based approach to mine candidate maximal co-locations and co-location instances; and (2) the co-location instances do not need to be stored after computing some characteristics of the corresponding co-location, which significantly reduces the execution time and space required for mining maximal co-locations. The performance study shows that the new method is efficient for mining both long and short co-location patterns, and is faster than some other methods (in particular the join-based method and the join-less method).

A new join-less approach for co-location pattern mining

With the rapid growth and extensive applications of the spatial dataset, itpsilas getting more important to solve how to find spatial knowledge automatically from spatial datasets. Spatial co-location patterns represent the subsets of features whose instances are frequently located together in geographic space. Itpsilas difficult to discovery co-location patterns because of the huge amount of data brought by the instances of spatial features. A large fraction of the computation time is devoted to generating the table instances of co-location patterns. The essence of co-location patterns discovery and three kinds of co-location patterns mining algorithms proposed in recent years are analyzed, and a new join-less approach for co-location patterns mining, which based on a data structure - CPI-tree (Co-location Pattern Instance Tree), is proposed. The CPI-tree materializes spatial neighbor relationships. All co-location table instances can be generated quickly with a CPI-tree. This paper proves the correctness and completeness of the new approach. Finally, an experimental evaluation using synthetic datasets and a real world dataset shows that the algorithm is computationally more efficient than the join-less algorithm.

A Review on Computational Trust Models for Multi-agent Systems

Trust plays important roles on effective interaction and cooperation for multi-agent systems(MAS). This study aims at finding out the current situation and future trends of computational trustfor multi-agent systems. Through defining seven common compositional elements for the computational trust models, the study points out significant weaknesses in the current design. Finally, the paper figures out the future research trends through discussion and analysis around the strengths and weaknesses identified. Also the paper proposes an idea of using ontology and XML technologies such as RDF that allow systems to provide both human and machine readable annotations for trust models.

A Banking Based Grid Recourse Allocation Scheduling

One of major bottlenecks in grid computing is grid resource allocation. There are many existing ways to solve the problem economical models are effective approaches to help manage and evaluate the resource allocation. Inspired by the banking marketing theory (BMT) comes a new way to study grid resources allocate. The key issues for meeting the requirement of BMT is try to find a best scheduling algorithm to deliver great value in the grid resource allocation. In this paper, the researcher found that the cost based scheduling algorithm is possible method to do that job. The essentially problem is pricing all the available resources in the transaction and maximum all participants based on the dynamic cost functions.

User Centred Mobile Aided Learning System: Student Response System (SRS)

This research develops a new system based on the user centred concepts and applied on the latest mobile devices. XML, database, information retrieval and object oriented technologies are embedded into the system. It is found that the system demonstrates a strong impact on teaching and learning in class activities in comparison with traditional learning environments. Also, the system has achieved that It can be self independent as well as integrated with other learning management environments, such as blackboard, Smartboard as well as subject oriented learning management systems, which makes an additional contribution to the modern pedagogical applications, such as activity based learning.

A service level agreement framework of cloud computing based on the Cloud Bank model

The Cloud Bank model, which is derived from Grid bank [1], is a kind of commerce model of cloud computing that provides pay-as-you-go computing resources. In this model, Cloud Bank is an agent platform of resource transaction. Cloud computing uses the concept of service level agreement (SLA) to control the use and receipt of computing resources from, and by, Cloud Bank. As computing resources are provided in the form of services, Quality of Service (QoS) mechanisms are introduced to solve any quality of service problems. This paper presents a framework of Service Level Agreements in the Cloud Bank model (CBSLA), QoS attributes is added to the CBSLA to guarantee the quality of service. All the transactions of cloud bank are based on the CBSLA agreement.

Learning with Mobile Technologies, Handheld Devices, and Smart Phones: Innovative Methods

Mobile Learning is a new trend in pedagogical communities. It matches the speed of fast moving methodologies in pedagogical world. The theories of activity-based learning, problem-based learning, work-based learning, and opinion-based learning, learner-centered learning, and so forth, can be integrated with these tiny handheld devices. Students and teachers communicate effectively and efficiently with these simple clicks to obtain the formative/informative and summative feedbacks. The learning outcomes for both ability and knowledge can be smartly measured and observed through the latest ICT technologies. Learning with Mobile Technologies, Handheld Devices and Smart Phones: Innovative Methods presents a collection of innovative research which focuses on learning in the digital world with advanced mobile technologies. This reference will aim to bring researchers, professors, and lectures and industrial training associations together to introduce a new era of teaching and learning societies.

Automatic Segmentation for Breast Skin-line

The accurate segmentation of breast in mammograms is critical for computer-aided diagnosis (CAD) of breast cancer. The challenges of breast segmentation come from tissue superimposition, low contrast and low visible breast boundary, noise areas and artifacts. In this research, a novel Automatic Breast Segmentation (ABS) approach was proposed. The experiment results showed that the proposed ABS approach can segment breast boundary reliably and accurately.

Schemaless approach of mapping XML document into Relational Database

The extensible Markup Language (XML) is used for representing and exchanging data through the Internet, but this technology needs a suitable medium for storing these data. At present, three common technologies can be used to store and retrieve XML documents, i.e., native XML database, Object Oriented Database (OODB) and Relational Database (RDB). This paper describes a general method for mapping XML documents to RDB. The method does not need a DTD or XML schema. And it can be applied as a general solution for any tree data structure and not just for XML data. Also, it can be used for data-centric and document-centric documents. Experiments on this method shows its ability to maintain document structure at a low cost price and easily, building of the original document is straight forward, performing first level semantic search is achievable either on a single document or on all documents.

The Optimum Font Size and Type for Students Aged 9-12 Reading Arabic Characters on Screen: A Case Study

More and more, interest in the way data is displayed on screen has increased, especially with the increase in the number of people using e-text for learning purposes. So, this requires more focus on factors that affect screen legibility. Text display factors, such as font size, line length and font type, have an impact on reading online. Two font types [Arabic Traditional and Simplified Arabic] in four different sizes [10, 14, 16 and 18] are measured using Arabic text. On-line processes were measured using reading–aloud technique. Accuracy of reading was also measured by the average of errors that students made when reading the text, while reading speed was tested by the time it took students to read the text. However, results indicated that Arabic text in font size 10 is not readable to students aged 10 to 12. On the other hand, font sizes sixteen and eighteen are more readable than any smaller-sized font, the averages of error size 18 improve in all font types, while age has a significant impact on reading speed. Simplified Arabic font is reported as readable to students aged 10-12, especially in sizes 14 and 18.